Krylov subspace methods as key building blocks for numerical linear algebra and optimization University of Antwerp
Solving a linear system of equations is undoubtedly one of the most fundamental tasks in numerical linear algebra and optimization. Not only are these linear systems often important on their own, they also appear frequently as sub-problems when attempting to solve a more complex problem. Many applications in science and industry can be modelled using a sparse matrix, i.e. containing only a limited amount of non-zero entries. Moreover, in many ...